Ming S.

Computation & Lab Technology Team, Sr Scientist Passionate about advancing protein engineering through integration of cutting-edge AI models with experimental research Key Contributions & Experience: > Designed and implemented AI protein engineering workflows, especially antibodies engineering, combining protein structure prediction and determination, de novo design, and the experimental feedback > Gained end-to-end experience across the protein engineering pipeline: from sequence/database mining and structural modeling to experimental structure determination and modeling simulations and AI-guided optimization > Developed and deployed protein design tools on AWS > Served as the scientific note-taker in cross-functional meetings involving in vivo and in vitro delivery Technical Focus Areas: > AI/ML for protein design (e.g., Alphafold, Boltz1/2, RFantibody, Antibody engineering etc ) > Structural biology pipelines (Cryo-EM imaging processing and modeling) > Molecular simulations and energy minimization > Scalable computing environments on AWS & GCP

Sr Scientist, Gene Editing Platform Technologies

Advisor: Dr. Joachim Frank Major projects : 1. Discovered dynamical structural features of malaria parasite ribosomes using cryo-EM single-particle methods 2. Co-developed new sample preparation method, microfluid mixing and spraying time-resolved cryo-EM, to capture transient states at the mili-second time scale 3. Contributed to statistical imaging analysis approaches' optimization and applied it to the time-resolved studies of ribosomal compositions

Advisor : Dr. Joachim Frank

Advisors: Dr. Ning Gao and Dr. Jianlin Lei